Modern recording technologies now enable simultaneous recording from large numbers of
neurons. This has driven the development of new statistical models for analyzing and …

The ability to generate high-fidelity synthetic data is crucial when available (real) data is
limited or where privacy and data protection standards allow only for limited use of the given …

Estimation of mutual information between random variables has become crucial in a range
of fields, from physics to neuroscience to finance. Estimating information accurately over a …

In order to deliver effective care, health management must consider the distinctive
trajectories of chronic diseases. These diseases recurrently undergo acute, unstable, and …

Quantile regression, the prediction of conditional quantiles, finds applications in various
fields. Often, some or all of the variables are discrete. The authors propose two new quantile …

Forest fires have become a national issue yearly and elicited serious attention from the
government and researchers in Indonesia. Copula-based joint distribution can construct a …

Neuronal circuits formed in the brain are complex with intricate connection patterns. Such
complexity is also observed in the retina with a relatively simple neuronal circuit. A retinal …

A major goal in neuroscience is to understand how populations of neurons code for stimuli
or actions. While the number of neurons that can be recorded simultaneously is increasing …

The $ k $ nearest neighbor algorithm ($ k $ NN) is one of the most popular nonparametric
methods used for various purposes, such as treatment effect estimation, missing value …

Recordings of complex neural population responses provide a unique opportunity for
advancing our understanding of neural information processing at multiple scales and …